Author: Yihua Xu Publisher: Open Dissertation Press ISBN: 9781361476444 Category : Languages : en Pages :
Book Description
This dissertation, "Procurement Risk Management Using Commodity Futures: a Multistage Stochastic Programming Approach" by Yihua, Xu, 許意華, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: ABSTRACT This study addresses the procurement risks that arise from variations in customer demand and fluctuations in the prices of material to be purchased, and seeks ways to effectively manage these risks. Procurement is prone to risks due to the uncertainties in, for example, demand, price and delivery. The effective management of these risks is hence a critical provision within the framework of procurement planning. However, what generally interests a procurement manager, when attempting to match closely product supply with customer demand, is the lowest cost that could possibly be attained. This mindset is found to concur with traditional models for procurement planning, which tend also to focus on cost minimization or the maximization of profit. With the potential risks largely ignored, such traditional models are clearly inadequate in the dynamic and precarious environment in which procurement is to be performed. This study describes a procurement planning approach that takes into account the risks arising from the fluctuations in procurement prices and customer demand volatility during a procurement undertaking. From the perspective of risk management, procurement is concerned with minimizing the downside risk exposure by means of hedging the associated risks so as to avoid possible losses. The specific risk hedging method developed in this study is based on the commodities and derivatives markets, which have grown rapidly and flourished in the age of e-commerce. This method is based on the static financial risk-hedging models that deal with a fixed hedged quantity. However, in making operational decisions in which the purchased quantity fluctuates due to customer demand, hedging has to be performed dynamically and this forms a significant extension to the available models. To allow and support operational procurement decision making as well as financial risk hedging in the presence of commodity markets, an integrated procurement risk management framework is developed. The development of this framework involves three major research issues (i) the establishment of a quantitative procurement risk management framework; (ii) the modelling of the stochastic behaviour of commodity prices and customer demand; and (iii) in II matching the two stochastic quantities mentioned above, the modelling of the procurement planning and financial risk hedging problem, jointly represented as a multistage stochastic program. The solutions obtained from this stochastic programming model can be evaluated according to the specified profit/risk profiles of a decision maker. To model the stochastic behaviour of commodity prices, the Gibson-Schwartz two-factor model and the Schwartz-Smith two-factor model are employed for storable commodities and non-storable commodities respectively. State-space form models and Kalman filtering are used to estimate the parameters of the empirical price models based on historical commodity price data. Two commodities are studied in this research. One is copper which is storable, and the other is electricity which is non-storable. Using the empirical price models, scenarios can be generated for stochastic program optimization. Numerical experiments are carried out to demonstrate the benefit that could be gained from the use of the integrated procurement risk management approach developed in this study. It is found that, when compared with pure operational pla
Author: Li Shi Publisher: Open Dissertation Press ISBN: 9781361310021 Category : Languages : en Pages :
Book Description
This dissertation, "Long-term Commodity Procurement Risk Management Using Futures Contracts: a Dynamic Stack-and-roll Approach" by Li, Shi, 时莉, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The procurement of commodity materials for production is an important issue in supply chain management. Effective procurement should consider both uncertain customer demand and fluctuating commodity price which, when act together, give rise to the procurement risk. To protect the bottom line, a manufacturer has to plan its procurement activities with special attention given to such procurement risk. Existing research has studied the use of exchange market-traded commodities in mitigating procurement risk. This study addresses the case of a manufacturer with long-term procurement commitments who wishes to hedge against the risk exposure by using long-dated futures contracts. In the commodities markets, however, long-dated futures are often illiquid or even unavailable, thus making the hedge ineffective. Alternatively, in a stack-and-roll hedge, the hedging positions are rolled forward in actively traded short-dated futures contracts of equal maturity until the procurement is executed. This in effect replicates the long-term futures contract in performing a hedge. This study therefore aims at developing a dynamic stack-and-roll approach that can effectively manage the long maturity procurement risk. The proposed dynamic stack-and-roll approach is inherently a discrete-time hedging strategy that divides the procurement planning horizon into multiple decision stages. The nearby futures are adopted as the short-dated futures as they are typically liquid. The hedging positions are adjusted periodically in response to the commodity price behaviour and updated information about the forward customer demand. For a manufacturer who wishes to mitigate the procurement risk as well as maximise the terminal revenue after the procurement, the mean-variance objective function is employed to model the manufacturer's risk aversion behaviour. Then, a dynamic program formulation of the approach is presented for determining a closed-form expression of the optimal hedging positions. Notice that the hedging policy is a time-consistent mean-variance policy in discrete-time, in contrast to the existing discrete hedging approaches that employ minimum-variance policies. In this study, the commodity prices are modelled by a fractal nonlinear regression process that employs a recurrent wavelet neural network as the nonlinear function. The purpose of this arrangement is to incorporate the fractal properties discovered in commodity prices series. In the wavelet transform domain, fractal self-similarity and self-affinity information of the price series over a certain time scale can be extracted. The Extended Kalman Filter (EKF) algorithm is applied to train the neural network for its lower training error comparing with classical gradient descent algorithms. Monthly returns and volatility of commodity prices are estimated by daily returns data in order to increase the estimation accuracy and facilitate effective hedging. The demand information is updated stage by stage using Bayesian inference. The updating process are defined and adapted to a filtration, which can be regarded as the information received at the beginning of each decision stage. Numerical experiments are carried out to evaluate the performance of the proposed stack-and-roll approach. The results show that the proposed approach robustly outperforms other hedging strategies that employ minimum-variance or nai
Author: Jian Ni Publisher: ISBN: 9781361254813 Category : Languages : en Pages :
Book Description
This dissertation, "Commodity Procurement Risk Management Using Futures Contracts: a Dynamic Financial Hedging Approach With Multistage Rebalancing" by Jian, Ni, 倪剑, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4658794 Subjects: Industrial procurement - Planning Risk management - Mathematical models
Author: Mingwei Liao Publisher: Open Dissertation Press ISBN: 9781361355602 Category : Languages : en Pages :
Book Description
This dissertation, "Futures Hedging on Both Procurement Risk and Sales Risk Under Correlated Prices and Demand" by Mingwei, Liao, 廖明瑋, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The profitability of a manufacturer could be largely affected by underlying uncertainties embedded in the fast-changing business environment. Random factors, such as input material price at the procurement end or output product price and demand at the sales end, might produce significant risks. Effective financial hedging therefore needs to be taken to mitigate these risk exposures. Although it is common to use commodity futures to control the risks at either end separately, little has been done on the hedging of these risk exposures in an integrated manner. Therefore, this study aims to develop a planning approach that performs financial hedging on both the procurement risk and the sales risk in a joint manner. This planning approach is based on a framework that has a risk-averse commodity processor that procures input commodity and sells output commodity in the spot market, while hedging the procurement risk and sales risk through trading futures contracts in the commodity markets. Both the input and output commodities futures are used for the hedging. A both-end-hedging model is developed to quantitatively evaluate the approach. The evaluation is based on an objective function that considers both profit maximisation and risk mitigation. Decisions on spot procurement, input futures hedging position, and output futures hedging position are optimised simultaneously. As the input commodity is the main production material for the output commodity, positive correlation between the input material price and the output product price is considered. The customer demand is considered negatively correlated with the output product price. An ethanol plant using corn as the main input material is employed as an example to implement the proposed model. The model is represented as a stochastic program, and the Gibson-Schwartz two-factor model is employed to describe the stochastic commodity prices. Historical commodity price data are used to estimate the parameters for the two-factor model with state-space form and Kalman filter. By generating various scenarios representing evolving prices and the random customer demand, the stochastic program could be solved using linear programming algorithms under its deterministic equivalent. Numerical experiments are carried out to demonstrate the benefit that could be gained from applying the both-end-hedging approach proposed in this study. Comparing with traditional no-hedging model or single-end-hedging models, the improvement obtained from the proposed model is found to be significant. The effectiveness of the model is further tested in various price trend and price correlation, demand elasticity and volatility, and risk attitude of the decision maker. It is found that the proposed approach is robust in these various circumstances, and the approach is especially effective when the price trend is uncertain and when the decision maker has a strong risk-averse attitude. DOI: 10.5353/th_b5270559 Subjects: Industrial procurement - Planning Risk management - Mathematical models Sales management
Author: Geoffrey Poitras Publisher: Routledge ISBN: 1136262601 Category : Business & Economics Languages : en Pages : 426
Book Description
Commodity Risk Management goes beyond just an introductory treatment of derivative securities, dealing with more advanced topics and approaching the subject matter from a unique perspective. At its core lies the concept that commodity risk management decisions require an in-depth understanding of speculative strategies, and vice versa. The book offers readers a unified treatment of important concepts and techniques that are useful in applying derivative securities in the management of risk in commodity markets. While some of these techniques are well known and fairly common, Poitras offers applications to specific situations and links to speculative trading strategies - extensions of the material that not only are hard to come by, but helpful to both the academic and the practitioner. The book is divided into three parts. The first part deals with the general framework for commodity risk management, the second part focuses on the use of derivative security contracts in commodity risk management, and the third part deals with applications to three specific situations. As a textbook, this book is designed to appeal to classes at a senior undergraduate/MBA/MA levelof training in Finance, financial economics, actuarial science, management science, agriculturaleconomics and accounting. There will also be interest for the book as: a monograph for research libraries, a handbook for individuals working in the commodity risk management industry, and a guidebook for those in the general public interested in topics like farm risk management or the assessment of hedging practices of publicly-traded commodity producers.
Author: John J. Stephens Publisher: Wiley ISBN: 9780471866251 Category : Business & Economics Languages : en Pages : 0
Book Description
Managing Commodity Risk is a clear and practical guide to managing commodity risk and explains how the commodity futures markets can be used to the manager's advantage. Beginning with a general overview of the definitions, processes and procedures, the book then explains in detail each of the individual approaches and looks at topics such as the commodity markets and their instruments, hedging with commodity futures and options and commodity futures exchanges. There is a checklist with key issues and approaches raised at the end of each chapter. This book is a practical primer for business managers who wish to manage and minimise the risk within their own industry.
Author: Helyette Geman Publisher: John Wiley & Sons ISBN: 0470740817 Category : Business & Economics Languages : en Pages : 320
Book Description
Commodities represent today the fastest growing markets worldwide. Historically misunderstood, generally under- studied and under- valued, certainly under- represented in the literature, commodities are suddenly receiving the attention they deserve. Bringing together some of the best authors in the field, this book focuses on the risk management issues associated with both soft and hard commodities: energy, weather, agriculturals, metals and shipping. Taking the reader through every part of the commodities markets, the authors discuss the intricacies of modelling spot and forward prices, as well as the design of new Futures markets. The book also looks at the use of options and other derivative contract forms for hedging purposes, as well as supply management in commodity markets. It looks at the implications for climate policy and climate research and analyzes the various freight derivatives markets and products used to manage shipping and freight risk in a global commodity world. It is required reading for energy and mining companies, utilities’ practitioners, commodity and cash derivatives traders in investment banks, CTA’s and hedge funds
Author: Yihua Xu
Author: Li Shi
Author: Yihua Xu (Ph. D.)
Author: Jian Ni
Author: Mingwei Liao
Author: Jian Ni (Ph. D.)
Author: 时莉
Author: Geoffrey Poitras
Author: John J. Stephens
Author: Helyette Geman